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Skills

R

Tidyverse

Python

Git

Docker

Bash

HPC (IBM LSF)



Highly experienced in designing and maintaining bioinformatic pipeline for large scale whole genome sequencing data


Disclaimer

Created with the R package pagedown.

Source code available at github/danangcrysnanto/cv.

Last updated on 2019-11-19.

Main

Danang Crysnanto

Interested in the bioinformatics of the large-scale whole-genome sequencing data. Current work first to propose the transition from linear to more representative, graph-based reference genome for unbiased sequence variant analysis.

Education

PhD Candidate in Computational Animal Genomics

Zurich Switzerland

Swiss Federal Institute of Technology (ETH Zurich)

Current - 2018

  • Research project: Graph-based genomic analysis
  • Skills learned: Graph analytics, Bioinformatics pipeline management
  • Adviser: Prof.Dr. Hubert Pausch

Msc in Quantitative Genetics and Genome Analysis

Edinburgh United Kingdom

The University of Edinburgh

2017 - 2016

  • Thesis: Widespread gene duplication in Drosophila RNAi pathways
  • Skills learned: Pylogenetic analysis, Bayesian statistics
  • Adviser: Dr. Darren Obbard
  • Best master thesis with distinction (all marks > 85)

Selected Publications

Accurate sequence variant genotyping in cattle using variation-aware genome graphs

Genetic Selection Evolution

N/A

2019

  • Danang Crysnanto and Hubert Pausch
  • Published in the first year of PhD
  • First work of using graphs for sequence variant discovery in livestock

Widespread gene duplication and adaptive evolution in the RNA-interference pathways of the Drosophila obscura group

BMC Evolutionary Biology

N/A

2019

  • Danang Crysnanto and Daren Obbard
  • Published from Master’s work
  • Identified massive gene duplications from analysis >30 Drosophila genome

Selected awards

Sir Kenneth Mather Memorial Prize

N/A

The Genetics Society

2018

  • Awarded annually based on the UK BSc, Msc and PhD thesis with an outstanding work in population genomics and quantitative genetics.

The Douglas Falconer Prize

N/A

The University of Edinburgh

2017

  • Awarded as the best Master’s thesis in the area of population genomics and quantitative genetics

Bronze Medalist 21st International Biology Olympiad (IBO)

Changwon South Korea

International Biology Olympiad

2010

  • International biology competition for high school students from 60 countries, who are winners of their respective National Biology Olympiad.

Selected conference and talks

Plant and Animal Genome (PAG) Conference

San Diego USA

N/A

2020

  • Talk title: Mapping sequencing read to bovine genome graph

Computational PANgenomics

Oeiras Portugal

Gulbekian Training Program in Bioinformatics

2019

  • Training with mini-hackaton on graph genomics

Genome Informatics and Livestock Genomics Conference

Cambridge United Kingdom

N/A

2018

  • Talk title: Assessment of the graph-based genotyping with bovine short-read data

52nd Population Genetics Group Conference

Oxford United Kingdom

N/A

2018

  • Talk title:Widespread gene duplication in Drosophila immune pathways (Invited talk)

Selected training

Nextflow for reproducible genomics

Tubingen Germany

Quantitative Biology Center (QBIC)

2019

  • Workshop on implementation of reproducible genomics

R packages

Swiss Institute of Bioinformatics

University of Zurich

2019

  • Training on creating R packages using devtools

Basic Tensorflow

Lausanne Switzerland

Google Zurich

2019

  • Training on basic machine learning in Swiss Applied Machine Learning Days

Docker for reproducible computational research

Swiss Institute of Bioinformatics

University of Bern

2018

  • Training on reproducibility genomic analysis using Docker

Bioinformatics of Long-Range Sequencing

Swiss Institute of Bioinformatics

University of Zurich

2018

  • Training on long-read (Pacbio and Nanopore) data analysis

Python for Life Science

Edinburgh United Kingdom

Edinburgh Genomics

2017

  • Using Python data science stack (e.g., Pandas, Jupyter) for genomics data analysis

High performance computing for genomics application

Scientific IT Services

ETH Zurich

2017

  • Training on best practice of using ETH big data clusterfor genomic application

GATK Best Practice for Genomic Data Analysis

Broad Institute

Harvard MA USA

2017

  • Training on the best practice variant discovery with Genomic analysis toolkit (GATK)